In order to ease the long driving on highways, intelligent computer based vehicles are necessary to recognize the contour of a road in real time. Towards this, one of the things that has been proposed in the literature is to provide optical or magnetic judging lines on driving ways for an optical sensor or magnetic sensor provided on the automobile to sense the judging lines. However, this requires providing judging lines on driving ways, and systems with magnetic/optical sensors are not universal.
It is also mentioned in the literature that high precision GPS can be used to find the position of a vehicle within the lane boundaries, with the help of map databases, for guidance and warning purposes. High accuracy GPS signals are expensive and if GPS is used for high-speed navigational purposes, then the frequency of the GPS signal needs to be high.
Some of the warning systems function much like adaptive cruise control and use a radar, sonar or laser beam to scan for potential obstacles and traffic changes to alert if a collision is imminent. Even though many techniques have been developed over the recent years for driving assistance, the idea of using visual information to achieve the same has become more and more popular in recent times. The use of on-board cameras and image processing of roadway scenes allow useful information to be gathered for vehicle navigation. Detecting lane boundaries is a core capability to implement advanced automotive functions such as collision warning, collision avoidance, and automatic vehicle guidance. If the lane boundaries and thus the road path can be detected, several other higher-level functions can be realized.
Varieties of methods are used in developing a vision system for intelligent vehicles. Some of these techniques are based on fuzzy control, transforms, edge gradients of lane markers, neural networks, feature tracking, and statistical methods. Statistical methods are generally based on classifying every pixel into road or non-road classes and determining road curvature based on such two-way classification. Such systems are generally not robust enough since the texture, width, color, and other features of road are quite diverse. Feature tracking relies strongly on the presence of certain artifacts in the scene such as lane markers and distinct edges, and irregularity in the presence of these artifacts limits the usability of such systems.
Some of the vision systems lack the capability to follow the road due to variations in road scenes over a wide range of possibilities. Roads typically have cracks, potholes, varying degrees of illumination including shadows and glare, obstructions such as other vehicles, rain, snow, dirt, or other foreign matter, that can cause a vision system to become disoriented.
Most of the vision-based systems require good lane markings and thus is limited to only those roads having good lane markings. The proposed invention extends the benefits of the computer vision system to provide guidance even in roads with moderate lane markings.